Data Engineer

Do you want to build the infrastructure that brings advanced analytics and AI from theory into reality? University College London Hospitals is looking for a Data Engineer (AI Enablement) to join the SAFEHR team. We are solving hard problems: building the secure, modern data infrastructure that lets advanced research and machine learning move from theory into reality. You will design data pipelines, evolve our data warehouse and metadata capabilities, prototype machine‑learning workflows on real clinical data, and support data quality across the Trust. Our stack includes R, Python, and SQL; with an ongoing move to a modern data platform. We develop our work as open source wherever feasible. You’ll work alongside clinicians, researchers, and engineers on projects that directly improve patient care.

Day to day, that means hands‑on data engineering: building and improving pipelines, coordinating metadata systems, mentoring junior staff, and working with clinical experts and researchers. This role would also be well suited to a research software engineer with an interest in data engineering. The position is classified at Grade 7, offering a competitive salary (£58,133 – £65,261). If you want real‑world data engineering challenges, serious technical development, and a direct line from your work to patient outcomes, we’d like to hear from you.

Main duties of the job

• Data Pipelines: You will design, build, and maintain data pipelines that give clinicians, researchers, and operational teams reliable, timely access to UCLH’s clinical data.
• Data Warehousing and Transformation: You will develop and improve UCLH’s data warehouse environments. Being involved in the transition from using an R‑based data pipeline to Spark jobs running on a data platform. You will model and transform data from our Epic electronic health record system, coordinating closely with stakeholders to maintain robust metadata. Where existing systems carry technical debt, you will be expected to show initiative in proposing and delivering re‑engineering work.
• Data Quality and Documentation: You will specify and build reports that measure data quality. You will also develop documentation that enables the scalable, correct use of clinical datasets by reporting teams, clinical users, and research projects.
• Collaboration and Open Source: You will work within a multidisciplinary team spanning engineers, clinicians, and data scientists, and collaborate with partners including UCL’s Advanced Research Computing Centre and UCLH’s Information Services teams. We develop our software as open source where feasible, and you will be expected to contribute to that culture through code reviews, automated testing, and clear, shareable code.